A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery
Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Chris Blenkinsopp and Katherine Brodie
Remote Sens. 2022, 14(3), 557; https://doi.org/10.3390/rs14030557
Received: 24 December 2021
/
Revised: 19 January 2022
/
Accepted: 21 January 2022
/
Published: 25 January 2022
(This article belongs to the Special Issue New Advances in Coastal Processes and Dynamics Using LiDAR)
This paper develops and validates a new fully automated procedure for shoreline delineation from high-resolution multispectral satellite images. The model is based on a new water–land index, the Direct Difference Water Index (DDWI). A new technique based on the buffer overlay method is also presented to determine the shoreline changes from different satellite images and obtain a time series for the shoreline changes. The shoreline detection model was applied to imagery from multiple satellites and validated to have sub-pixel accuracy using beach survey data that were collected from the Lake Michigan (USA) shoreline using a novel backpack-based LiDAR system. The model was also applied to 132 satellite images of a Lake Michigan beach over a three-year period and detected the shoreline accurately, with a >99% success rate. The model out-performed other existing shoreline detection algorithms based on different water indices and clustering techniques. The resolution shoreline position timeseries is the first satellite image-extracted dataset of its kind in terms of its high spatial and temporal resolution, and paves the road to obtaining other high-temporal-resolution datasets to refine models of beaches worldwide.
View Full-Text
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Abdelhady, H.U.; Troy, C.D.; Habib, A.; Manish, R. A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery. Remote Sens. 2022, 14, 557. https://doi.org/10.3390/rs14030557
AMA Style
Abdelhady HU, Troy CD, Habib A, Manish R. A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery. Remote Sensing. 2022; 14(3):557. https://doi.org/10.3390/rs14030557
Chicago/Turabian StyleAbdelhady, Hazem U., Cary D. Troy, Ayman Habib, and Raja Manish. 2022. "A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery" Remote Sensing 14, no. 3: 557. https://doi.org/10.3390/rs14030557
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
